A decade of rapid technological advances has provided an exciting opportunity to incorporate information relating to a range of potentially important disease determinants in the clinical decision-making process. Access to highly detailed data will enable respiratory medicine to evolve from one-size-fits-all models of care, which are associated with variable clinical effectiveness and high rates of side-effects, to precision approaches, where treatment is tailored to individual patients. The human microbiome has increasingly been recognised as playing an important part in determining disease course and response to treatment. Its inclusion in precision models of respiratory medicine, therefore, is essential. Analysis of the microbiome provides an opportunity to develop novel prognostic markers for airways disease, improve definition of clinical phenotypes, develop additional guidance to aid treatment selection, and increase the accuracy of indicators of treatment effect. In this Review we propose that collaboration between researchers and clinicians is needed if respiratory medicine is to replicate the successes of precision medicine seen in other clinical specialties.
Introduction
The advent of precision medicine makes the next 10 years of clinical medicine incredibly exciting. With the availability of more detailed and comprehensive information on which to base treatment decisions, positive clinical outcomes become increasingly likely. A personalised or precision approach to medicine involves taking into account factors specific to an individual patient that identify the nature of their disease or disorder and the interventions that are most likely to be beneficial. The importance of such an approach might seem obvious, but efforts to standardise treatment and to ensure consistent levels of care, and the time required to assess wider contributors to disease, have meant that therapy is commonly defined by guidelines based on grouped clinical or physiological characteristics. This one-size-fits-all model of care makes the assumption that all patients with the same disorder, which could have arisen via several different pathways, will respond equally well to the same treatments. Furthermore, this approach necessarily accepts that treatment will be less than optimum for any but the average patient, and that side-effects, some severe, will occur in a substantial proportion of individuals.
The benefits of precision medicine have been shown clearly in relation to cancer. Technological advances over the past four decades have provided the ability to assess genetic material quickly and cheaply. In turn, it has become possible to tailor treatment to specific cancer genotypes.1 Recognition of the importance of this strategy has culminated in the National Institute of Health Precision Medicine Initiative Cohort Program. This project aims to build on the successful use of patients' genetic information to guide further improvements in cancer prevention and treatment.2
Despite the current high profile of personalised cancer therapy, oncology is a relative newcomer to precision medicine. By contrast, a precision approach has been the foundation of infectious disease management for well over a century,3 being based on the identification of causal agents and their antimicrobial susceptibility through axenic culture. Such culture-based analysis is widespread in respiratory medicine, including in disorders such as cystic fibrosis and chronic obstructive pulmonary disease (COPD).
Despite the importance of diagnostic microbiology, most respiratory clinicians would regard the use of patients' genetics to develop specific pharmacotherapies for cystic fibrosis, as the most high-profile example of precision medicine in respiratory disease. While giving rise to broadly comparable clinical phenotypes, nearly 2000 mutations in CFTR have been identified and represent an array of pathophysiological pathways and potential therapeutic targets, the complexity of which is compounded by around 40% of patients with cystic fibrosis being complex heterozygotes.4 The success of the CFTR potentiator, ivacaftor, in improving ion-channel regulation in patients with class III mutations (especially Gly551Asp) has been greatly encouraging.5 Research to identify agents, alone or in combination, that are effective for other genotypes in cystic fibrosis is continuing.6 Nevertheless, despite such success, the potential benefits of extending precision respiratory medicine beyond human genetics are clear. Even in a disorder such as cystic fibrosis, which results from a genetic mutation, genotype only explains around 50% of variation in pulmonary function. The remaining 50% is accounted for by stochastic and deterministic environmental influences,7 a substantial component of which is likely to stem from airway microbiology. Furthermore, the contribution of microbiological factors to differences between patients in disease course is probably even greater in disorders such as asthma and COPD, which have no overarching genetic basis, and where patients are grouped according to broad clinical and physiological characteristics.8
Key messages
•
The drive to improve clinical outcomes and reduce adverse events in respiratory medicine is becoming increasingly focused on precision approaches
•
Accumulating evidence suggests that interactions between host and microbiome contribute substantially to differences in clinical phenotypes and disease courses between patients
•
The potential for microbiome analysis to help stratify treatment and provide prognostic insight is beginning to be seen for several respiratory disorders
•
Continuing technological advances in areas such as metatranscriptomics and metabolomics are set to provide increasingly detailed and potentially informative data
•
The effective translation of microbiome analysis into precision models of respiratory care now requires concerted collaboration between researchers across various clinical and research disciplines
The detection of certain pathogens in airway samples can provide important prognostic markers and therapeutic targets for acute and chronic infections.9, 10 Why microbiological data have not featured more prominently in efforts to personalise respiratory medicine, therefore, needs to be considered. Exclusion is due mostly to the limitations of culture-based microbiology as applied diagnostically. Many common respiratory pathogens can exhibit phenotypes that limit their detection with standard protocols,11 whereas others, including strict anaerobes, require specialised sample-handling and growth conditions. Well described disparities between antibiotic susceptibility in vitro and treatment efficacy in vivo have led to the usefulness of routine testing in many chronic respiratory infections being questioned,12 with growing reliance on standardised antibiotic combinations. Arguably, with increasingly dogmatic approaches to treatment, a move has been seen away from precision respiratory medicine. Furthermore, although culture-based characterisation of individual pathogens can provide important insights into the likely disease course and clinical outcomes,13 axenic culture removes the potential for interspecies interactions that affect pathogen growth and virulence.14
Advances in DNA sequencing technology has, in parallel, led to progress in precision medicine and characterisation of complex microbial systems. Costs of microbiological analysis have not only reduced, but the use of sequencing for research has broadened, leading to substantial analytical and conceptual progress. By addressing many of the historical limitations of culture-based microbiology, sequencing approaches provide an opportunity to improve understanding of an important group of potential disease determinants—the complex microbial systems that are intimately associated with the human body.
In this Review, we make the case that rapid access to high-quality correlated respiratory microbiome information will add substantially to physicians' ability to make precise patient-centred treatment decisions. We discuss the evidence for the role of the human microbiome in respiratory disease, the implications for clinical decision making, and the importance of forging an effective link between advances in basic science and health-care delivery.
Section snippets
The human microbiome
The microbes that comprise the human microbiome are ecologically and immunologically integrated with our bodies, vastly exceeding our own cells both in number and genetic complexity.15 These intricate and interactive microbial networks, which consist of bacteria, fungi, viruses, bacteriophages, archaea, and eukaryotes, colonise niches all over the body. Unlike our genome, our microbiome is highly dynamic, changing as we grow and age,16 is spatially differentiated (ie, can be differentiated from
The respiratory microbiome as a guide to treatment
The compositions of the various microbiota in the human body are determined by the selective characteristics of the niches in which they grow.17 The lower airways, however, comprise a special case. Although exposed to the external environment and adjoining regions with commensal colonies, the lower airways are believed to be free from substantial resident microbial populations under normal circumstances, due to continual clearance through mucociliary action and phagocytosis preventing
The wider human microbiome and respiratory health
The interactions that occur between all mucosae and the microbiome are important determinants of general health.85 The role of the gut microbiota in the development and regulation of immunity in particular86, 87 suggests that these interactions contribute to differences in respiratory disease courses between individuals. We discuss here the effect of host–microbiome interactions in early life and how they affect immune regulation. We also explore the role of microbiota outside the lower
Challenges
The technological capacity available to analyse the microbiome is evolving rapidly. 16S rRNA gene sequencing is increasingly being replaced by more discriminatory shotgun metagenomic sequencing, which can accurately identify microbes and provide information on pathogenicity and antibiotic resistance markers. In turn, metatranscriptomic and metabolomic approaches that characterise microbial behaviour in response to changes in disease or therapy and capture an increased proportion of the
Conclusions and the future
Recognition of the importance of microbiome analysis is still growing, but it has clear potential to guide treatment, which suggests that it could become a central component in the management of respiratory disease, from first presentation to end stage or transplantation. For example, we suggest that in the near term, the ability to compare airway microbiota profiles with databases compiled from large groups of patients would increase accuracy of subtyping of respiratory conditions, and provide
Search strategy and selection criteria
References for this review were identified through searches of PubMed for articles published from January, 1971, to October, 2015, by use of the terms “asthma”, “COPD”, “cystic fibrosis”, “dysbiosis”, “idiopathic pulmonary fibrosis”, “infection”, “microbiome”, “microbiota”, “personalized”, “precision”, and “respiratory”. Articles resulting from these searches and relevant references cited in those articles were reviewed. Only English-language articles were included.
Personalizing oncology: perspectives and prospects
J Clin Oncol
(2013)
FS Collins et al.
A new initiative on precision medicine
N Engl J Med
(2015)
GB Rogers et al.
Studying bacterial infections through culture-independent approaches
J Med Microbiol
(2009)
Patient registry: 2013 annual data report to the center directors, Bethesda, MD, USA
JM Collaco et al.
Quantification of the relative contribution of environmental and genetic factors to variation in cystic fibrosis lung function
J Pediatr
(2010)
SE Wenzel
Asthma phenotypes: the evolution from clinical to molecular approaches
Nat Med
(2012)
JM Courtney et al.
Predictors of mortality in adults with cystic fibrosis
Pediatr Pulmonol
(2007)
DJ Wolter et al.
Staphylococcus aureus small-colony variants are independently associated with worse lung disease in children with cystic fibrosis
Clin Infect Dis
(2013)
N Mayer-Hamblett et al.
Pseudomonas aeruginosa in vitro phenotypes distinguish cystic fibrosis infection stages and outcomes
Am J Respir Crit Care Med
(2014)
Structure, function and diversity of the healthy human microbiome
Nature
(2012)
T Yatsunenko et al.
Human gut microbiome viewed across age and geography
Nature
(2012)
EA Grice et al.
The skin microbiome
Nat Rev Microbiol
(2011)
AM Stringer et al.
Biomarkers of chemotherapy-induced diarrhoea: a clinical study of intestinal microbiome alterations, inflammation and circulating matrix metalloproteinases
Support Care Cancer
(2013)
SS Kang et al.
Diet and exercise orthogonally alter the gut microbiome and reveal independent associations with anxiety and cognition
Mol Neurodegener
(2014)
JM Allen et al.
Voluntary and forced exercise differentially alters the gut microbiome in C57BL/6J mice
J Appl Physiol (1985)
(2015)
AS Neish
Mucosal immunity and the microbiome
Ann Am Thorac Soc
(2014)
M Lyte
Microbial endocrinology in the microbiome-gut-brain axis: how bacterial production and utilization of neurochemicals influence behavior
PLoS Pathog
(2013)
AL Kau et al.
Human nutrition, the gut microbiome and the immune system
Nature
(2011)
M Vijay-Kumar et al.
Metabolic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5
Science
(2010)
PJ Turnbaugh et al.
An obesity-associated gut microbiome with increased capacity for energy harvest
Nature
(2006)
X Zhang et al.
The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment
Nat Med
(2015)
EA Mayer et al.
Gut microbes and the brain: paradigm shift in neuroscience
J Neurosci
(2014)
ES Charlson et al.
Topographical continuity of bacterial populations in the healthy human respiratory tract
Am J Respir Crit Care Med
(2011)
A Morris et al.
Comparison of the respiratory microbiome in healthy nonsmokers and smokers
For instance, the ability to screen and select personalized cancer drugs based on a particular patient's mutation(s) results in improved overall prognosis (Friedman et al., 2015). Consequently, “precision medicine,” which refers to optimizing dosage (both timing of and concentration) of the optimal drug(s), has attracted considerable interest and already made substantial impacts (Jameson and Longo 2015; Rogers and Wesselingh 2016). This discipline is particularly important in antibiotic therapy given the rise of multi-drug-resistant (MDR) bacteria (Tamma et al., 2012); tailored administration of antibiotics in a scientifically validated manner may, then, both lead to better response to treatment and potentially thwart further generation of MDR microbes.
This study reports an integrated microfluidic device that was capable of executing rapid antimicrobial susceptibility tests with one, two, or even three antibiotics against two clinically isolated multi-drug-resistant bacteria strains (including carbapenem-resistant Escherichia coli and methicillin-resistant Staphylococcus aureus). Bacteria were automatically mixed for 10 min with serially diluted antibiotics with a novel, membrane-type micromixer consisting of two circular micropumps, and the minimum inhibitory concentrations (MIC) were then determined via simple colorimetric reactions in only 4.5–6 h using only 3 μL of bacteria sample of each reaction (as opposed to 24 h and 50 μL, respectively, with the conventional broth micro-dilution method). In addition to determining MICs of antibiotics (ceftazidime, gentamicin, meropenem, vancomycin and linezolid), interaction effects across antibiotics combinations (gentamicin/meropenem or ceftazidime/gentamicin/meropenem) at different dosages were explored. The efficacy of polypharmacy showed additivity when gentamicin or ceftazidime/gentamicin were combined with meropenem to treat carbapenem-resistant Escherichia coli. This represents the first time that the perplexing clinical decision to choose multiple antibiotics for combination therapy against drug resistant bacteria can be realized on an integrated microfluidic device within 6 h.
2020, International Journal of Pediatric Otorhinolaryngology
Citation Excerpt :
However, standard PCR methods can only detect known bacteria, and therefore cannot reveal the full range of microbial diversity. New sequencing technologies, such as 16S ribosomal RNA (16S rRNA) gene sequencing, are being increasingly used as an alternative to standard culture techniques for microbial identification [10]. Moreover, 16S rRNA amplicon analyses remain the standard approach for identifying microbial diversity.
Otitis media with effusion (OME) is one of the most common pediatric diseases worldwide. Several studies have analyzed the diversity of the microbiomes found in the middle ear effusions (MEEs) of populations from developed countries. However, no microbiological studies of MEEs from Chinese children with OME have been reported. This study investigated the middle ear and adenoid microbiological profiles of children with OME, and compared the microbial flora of the adenoid between children with and without otitis media.
MEEs and adenoid swabs were acquired from 15 children undergoing ventilation tube insertion and adenoidectomy. Adenoid swabs from 15 patients with no ear disease were used as controls. Samples were analyzed by 16S rRNA sequencing. Operational taxonomic units (OTUs) abundance information were normalized. Alpha diversity analyses were used to assess the richness and diversity of the microbial community for each sample. Beta diversity analyses were used to determine the inter-group variability between microbiome structure.
Based on the mean relative abundance, the MEEs were dominated by Haemophilus (14.75%), Staphylococcus (9.37%) and Halomonas (7.85%), and the bacterial compositions of the adenoids in the OME groups were dominated by Haemophilus (21.87%), Streptococcus (19.65%), and Neisseria (5.8%). The bacterial compositions in the adenoids of the controls were dominated by Haemophilus (15.96%), Streptococcus (13.33%), and Moraxella (12.28%).
Alpha diversity analyses showed that there were no significant differences in microbiome richness or diversity between the middle ear effusions (TM) and adenoids (TA) of OME subjects. Adenoid samples from OME patients (TA) and control patients (CA) were also similar. Beta diversity analyses showed that the microbiomes of the adenoids in OME patients were also similar to that of controls. However, the microbiome structure of middle ear effusions was dissimilar to those of the adenoids in OME patients according to beta diversity analyses.
Our results confirmed the microbial diversity of MEEs among Chinese children. However, the dissimilar microbiome composition between samples taken from the surface of the adenoids and from the middle ear effusions challenges the conventional theory that the adenoid serves as a microbial reservoir in children with otitis media with effusion.
It is clear from studies of other species that microbial populations are crucial in modulating host immune defenses; this, in turn, influences respiratory homeostasis. The successful communications between the mucosal microbiota and their host immune system (Figure 2) are essential in regulation of mucosal immunity and maintenance of metabolic homoeostasis [62]. While the detailed structure and function of the respiratory mucosal immune system [6] is beyond the scope of this review, a better understanding of the nature of interaction between mucosal microbiota, epithelium, and immune cells is essential in determining the factors that shape the resident microbial population.
Recognizing the respiratory tract as a dynamic and complex ecosystem has enhanced our understanding of the pathophysiology of bovine respiratory disease (BRD). There is widespread evidence showing that disease-predisposing factors often disrupt the respiratory microbial ecosystem, provoking atypical colonization patterns and a progressive dysbiosis. The ecological factors that shape the respiratory microbiota, and the influence of these complex communities on bovine respiratory health, are a rich area for research exploration. Here, we review the current status of understanding of the bovine respiratory microbiota, the factors that influence its development and stability, its role in maintaining mucosal homeostasis, and ultimately its contribution to bovine health and disease. Finally, we explore the limitations of current research approaches to the microbiome and discuss potential directions for future research that can help us better understand the role of the respiratory microbiota in the health, welfare, and productivity of livestock.
2019, Kendig's Disorders of the Respiratory Tract in Children
A wide variety of microorganisms are potential respiratory pathogens, and the spectrum of known pathogens for each respiratory infection syndrome has not changed markers over recent years. Detection of likely etiologic agents of respiratory infections can help direct management and can also play an important role in disease surveillance. For this purpose, we are still reliant on many traditional diagnostic tools that have been used for decades in order to determine the microbial etiology of respiratory infections. However, these tools have been increasingly supplemented by newer methods, particular molecular diagnostic techniques, which have enabled the more rapid detection of many pathogens that were previously difficult to detect. These advances have particularly lead to improvements in the ability to detect respiratory viruses and also other microorganisms that do not normally colonize the respiratory tract. Recognition of the existence of the lung microbiome has challenged the traditional views of pneumonia pathogenesis and may provide the opportunity for new diagnostic tools that are focused on more than just detection of specific known pathogens. Continued liaison between clinicians and laboratory staff is vital in order to facilitate the most cost-effective use of laboratory diagnostics.
In this review, we outline novel approaches to bronchiectasis management in adults.4 We suggest that randomised trials might not have shown clinical benefit because of the heterogeneity of bronchiectasis, and discuss how a logical stratified approach to treatment will be required going forward.16 In this light, we offer novel perspectives on strategies for patients' stratification that could facilitate personalised care in the future.
European Respiratory Society guidelines for the management of adult bronchiectasis highlight the paucity of treatment options available for patients with this disorder. No treatments have been licensed by regulatory agencies worldwide, and most therapies used in clinical practice are based on very little evidence. Development of new treatments is needed urgently. We did a systematic review of scientific literature and clinical trial registries to identify agents in early-to-late clinical development for bronchiectasis in adults. In this Review, we discuss the mechanisms and potential roles of emerging therapies, including drugs that target airway and systemic inflammation, mucociliary clearance, and epithelial dysfunction. To ensure these treatments achieve success in randomised clinical trials—and therefore reach patients—we propose a reassessment of the current approach to bronchiectasis. Although understanding of the pathophysiology of bronchiectasis is at an early stage, we argue that bronchiectasis is a heterogeneous disease with many different biological mechanisms that drive disease progression (endotypes), and therefore the so-called treatable traits approach used in asthma and chronic obstructive pulmonary disease could be applied to bronchiectasis, with future trials targeted at the specific disease subgroups most likely to benefit.